Use ArrayLike and NDArray wherever possible. Some type fixes and some related corner cases

masque/builder/devices.py

@@ -6,14 +6,14 @@ import traceback
 import logging
 from collections import Counter
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi
-from numpy.typing import ArrayLike
+from numpy.typing import ArrayLike, NDArray
 
 from ..pattern import Pattern
 from ..subpattern import SubPattern
 from ..traits import PositionableImpl, Rotatable, PivotableImpl, Copyable, Mirrorable
-from ..utils import AutoSlots, rotation_matrix_2d, vector2
+from ..utils import AutoSlots, rotation_matrix_2d
 from ..error import DeviceError
 
 
@@ -48,11 +48,12 @@ class Port(PositionableImpl, Rotatable, PivotableImpl, Copyable, Mirrorable, met
     ptype: str
     """ Port types must match to be plugged together if both are non-zero """
 
-    def __init__(self,
-                 offset: ArrayLike,
-                 rotation: Optional[float],
-                 ptype: str = 'unk',
-                 ) -> None:
+    def __init__(
+            self,
+            offset: ArrayLike,
+            rotation: Optional[float],
+            ptype: str = 'unk',
+            ) -> None:
         self.offset = offset
         self.rotation = rotation
         self.ptype = ptype
@@ -63,7 +64,7 @@ class Port(PositionableImpl, Rotatable, PivotableImpl, Copyable, Mirrorable, met
         return self._rotation
 
     @rotation.setter
-    def rotation(self, val: float):
+    def rotation(self, val: float) -> None:
         if val is None:
             self._rotation = None
         else:
@@ -207,6 +208,21 @@ class Device(Copyable, Mirrorable):
     def __getitem__(self, key: Union[List[str], Tuple[str], KeysView[str], ValuesView[str]]) -> Dict[str, Port]:
         pass
 
+#=======
+##    from typing import overload
+##    from _collections_abc import dict_keys, dict_values
+##
+##    @overload
+##    def __getitem__(self, key: str) -> Port:
+##        pass
+##
+##    @overload
+##    def __getitem__(self, key: Union[List[str], Tuple[str], dict_keys[str, str], dict_values[str, str]]) -> Dict[str, Port]:
+###    def __getitem__(self, key: Iterable[str]) -> Dict[str, Port]:
+##        pass
+#
+##    def __getitem__(self, key: Union[str, Iterable[str]]) -> Union[Port, Dict[str, Port]]:
+#    def __getitem__(self, key: Union[str, Iterable[str]]) -> Any:
     def __getitem__(self, key: Union[str, Iterable[str]]) -> Union[Port, Dict[str, Port]]:
         """
         For convenience, ports can be read out using square brackets:
@@ -504,9 +520,9 @@ class Device(Copyable, Mirrorable):
             self: D,
             other: O,
             *,
-            offset: vector2 = (0, 0),
+            offset: ArrayLike = (0, 0),
             rotation: float = 0,
-            pivot: vector2 = (0, 0),
+            pivot: ArrayLike = (0, 0),
             mirrored: Tuple[bool, bool] = (False, False),
             port_map: Optional[Dict[str, Optional[str]]] = None,
             skip_port_check: bool = False,
@@ -585,7 +601,7 @@ class Device(Copyable, Mirrorable):
             *,
             mirrored: Tuple[bool, bool] = (False, False),
             set_rotation: Optional[bool] = None,
-            ) -> Tuple[numpy.ndarray, float, numpy.ndarray]:
+            ) -> Tuple[NDArray[numpy.float64], float, NDArray[numpy.float64]]:
         """
         Given a device `other` and a mapping `map_in` specifying port connections,
           find the transform which will correctly align the specified ports.
@@ -668,7 +684,7 @@ class Device(Copyable, Mirrorable):
 
         return translations[0], rotations[0], o_offsets[0]
 
-    def translate(self: D, offset: vector2) -> D:
+    def translate(self: D, offset: ArrayLike) -> D:
         """
         Translate the pattern and all ports.
 
@@ -683,7 +699,7 @@ class Device(Copyable, Mirrorable):
             port.translate(offset)
         return self
 
-    def rotate_around(self: D, pivot: vector2, angle: float) -> D:
+    def rotate_around(self: D, pivot: ArrayLike, angle: float) -> D:
         """
         Translate the pattern and all ports.
 
@@ -753,10 +769,10 @@ class Device(Copyable, Mirrorable):
 
 
 def rotate_offsets_around(
-        offsets: ArrayLike,
-        pivot: ArrayLike,
+        offsets: NDArray[numpy.float64],
+        pivot: NDArray[numpy.float64],
         angle: float,
-        ) -> numpy.ndarray:
+        ) -> NDArray[numpy.float64]:
     offsets -= pivot
     offsets[:] = (rotation_matrix_2d(angle) @ offsets.T).T
     offsets += pivot

masque/builder/utils.py

@@ -1,11 +1,12 @@
 from typing import Dict, Tuple, List, Optional, Union, Any, cast, Sequence
 from pprint import pformat
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi
+from numpy.typing import ArrayLike
 
 from .devices import Port
-from ..utils import rotation_matrix_2d, vector2
+from ..utils import rotation_matrix_2d
 from ..error import BuildError
 
 
@@ -13,9 +14,9 @@ def ell(
         ports: Dict[str, Port],
         ccw: Optional[bool],
         bound_type: str,
-        bound: Union[float, vector2],
+        bound: Union[float, ArrayLike],
         *,
-        spacing: Optional[Union[float, numpy.ndarray]] = None,
+        spacing: Optional[Union[float, ArrayLike]] = None,
         set_rotation: Optional[float] = None,
         ) -> Dict[str, float]:
     """
@@ -96,8 +97,11 @@ def ell(
         rotations[~has_rotation] = rotations[has_rotation][0]
 
         if not numpy.allclose(rotations[0], rotations):
+            port_rotations = {k: numpy.rad2deg(p.rotation) if p.rotation is not None else None
+                              for k, p in ports.items()}
+
             raise BuildError('Asked to find aggregation for ports that face in different directions:\n'
-                             + pformat({k: numpy.rad2deg(p.rotation) for k, p in ports.items()}))
+                             + pformat(port_rotations))
     else:
         if set_rotation is not None:
             raise BuildError('set_rotation must be specified if no ports have rotations!')

masque/file/gdsii.py

@@ -30,7 +30,8 @@ import logging
 import pathlib
 import gzip
 
-import numpy        # type: ignore
+import numpy
+from numpy.typing import NDArray
 import klamath
 from klamath import records
 
@@ -369,10 +370,12 @@ def _subpatterns_to_refs(subpatterns: List[SubPattern]) -> List[klamath.library.
         properties = _annotations_to_properties(subpat.annotations, 512)
 
         if isinstance(rep, Grid):
-            xy = numpy.array(subpat.offset) + [
+            b_vector = rep.b_vector if rep.b_vector is not None else numpy.zeros(2)
+            b_count = rep.b_count if rep.b_count is not None else 1
+            xy: NDArray[numpy.float64] = numpy.array(subpat.offset) + [
                 [0, 0],
                 rep.a_vector * rep.a_count,
-                rep.b_vector * rep.b_count,
+                b_vector * b_count,
                 ]
             aref = klamath.library.Reference(struct_name=encoded_name,
                                              xy=numpy.round(xy).astype(int),

masque/file/oasis.py

@@ -198,8 +198,7 @@ def writefile(
         open_func = open
 
     with io.BufferedWriter(open_func(path, mode='wb')) as stream:
-        results = write(patterns, stream, *args, **kwargs)
-    return results
+        write(patterns, stream, *args, **kwargs)
 
 
 def readfile(
@@ -491,10 +490,14 @@ def _placement_to_subpat(placement: fatrec.Placement, lib: fatamorgana.OasisLayo
     pname = placement.get_name()
     name = pname if isinstance(pname, int) else pname.string
     annotations = properties_to_annotations(placement.properties, lib.propnames, lib.propstrings)
+    if placement.angle is None:
+        rotation = 0
+    else:
+        rotation = numpy.deg2rad(float(placement.angle))
     subpat = SubPattern(offset=xy,
                         pattern=None,
                         mirrored=(placement.flip, False),
-                        rotation=numpy.deg2rad(placement.angle),
+                        rotation=rotation,
                         scale=float(mag),
                         identifier=(name,),
                         repetition=repetition_fata2masq(placement.repetition),

masque/file/python_gdsii.py

@@ -28,11 +28,12 @@ import logging
 import pathlib
 import gzip
 
-import numpy        # type: ignore
+import numpy
+from numpy.typing import ArrayLike, NDArray
 # python-gdsii
-import gdsii.library
-import gdsii.structure
-import gdsii.elements
+import gdsii.library    #type: ignore
+import gdsii.structure  #type: ignore
+import gdsii.elements   #type: ignore
 
 from .utils import clean_pattern_vertices, is_gzipped
 from .. import Pattern, SubPattern, PatternError, Label, Shape
@@ -182,8 +183,7 @@ def writefile(
         open_func = open
 
     with io.BufferedWriter(open_func(path, mode='wb')) as stream:
-        results = write(patterns, stream, *args, **kwargs)
-    return results
+        write(patterns, stream, *args, **kwargs)
 
 
 def readfile(
@@ -402,10 +402,12 @@ def _subpatterns_to_refs(
         new_refs: List[Union[gdsii.elements.SRef, gdsii.elements.ARef]]
         ref: Union[gdsii.elements.SRef, gdsii.elements.ARef]
         if isinstance(rep, Grid):
-            xy = numpy.array(subpat.offset) + [
+            b_vector = rep.b_vector if rep.b_vector is not None else numpy.zeros(2)
+            b_count = rep.b_count if rep.b_count is not None else 1
+            xy: NDArray[numpy.float64] = numpy.array(subpat.offset) + [
                 [0, 0],
                 rep.a_vector * rep.a_count,
-                rep.b_vector * rep.b_count,
+                b_vector * b_count,
                 ]
             ref = gdsii.elements.ARef(struct_name=encoded_name,
                                       xy=numpy.round(xy).astype(int),

masque/file/svg.py

@@ -4,7 +4,8 @@ SVG file format readers and writers
 from typing import Dict, Optional
 import warnings
 
-import numpy        # type: ignore
+import numpy
+from numpy.typing import ArrayLike
 import svgwrite     # type: ignore
 
 from .utils import mangle_name
@@ -141,7 +142,7 @@ def writefile_inverted(pattern: Pattern, filename: str):
     svg.save()
 
 
-def poly2path(vertices: numpy.ndarray) -> str:
+def poly2path(vertices: ArrayLike) -> str:
     """
     Create an SVG path string from an Nx2 list of vertices.
 
@@ -151,8 +152,9 @@ def poly2path(vertices: numpy.ndarray) -> str:
     Returns:
         SVG path-string.
     """
-    commands = 'M{:g},{:g} '.format(vertices[0][0], vertices[0][1])
-    for vertex in vertices[1:]:
+    verts = numpy.array(vertices, copy=False)
+    commands = 'M{:g},{:g} '.format(verts[0][0], verts[0][1])
+    for vertex in verts[1:]:
         commands += 'L{:g},{:g}'.format(vertex[0], vertex[1])
     commands += ' Z   '
     return commands

masque/label.py

@@ -1,9 +1,11 @@
 from typing import Tuple, Dict, Optional, TypeVar
 import copy
-import numpy        # type: ignore
+
+import numpy
+from numpy.typing import ArrayLike, NDArray
 
 from .repetition import Repetition
-from .utils import vector2, rotation_matrix_2d, layer_t, AutoSlots, annotations_t
+from .utils import rotation_matrix_2d, layer_t, AutoSlots, annotations_t
 from .traits import PositionableImpl, LayerableImpl, Copyable, Pivotable, LockableImpl, RepeatableImpl
 from .traits import AnnotatableImpl
 
@@ -43,7 +45,7 @@ class Label(PositionableImpl, LayerableImpl, LockableImpl, RepeatableImpl, Annot
             self,
             string: str,
             *,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             layer: layer_t = 0,
             repetition: Optional[Repetition] = None,
             annotations: Optional[annotations_t] = None,
@@ -74,7 +76,7 @@ class Label(PositionableImpl, LayerableImpl, LockableImpl, RepeatableImpl, Annot
         new.set_locked(self.locked)
         return new
 
-    def rotate_around(self: L, pivot: vector2, rotation: float) -> L:
+    def rotate_around(self: L, pivot: ArrayLike, rotation: float) -> L:
         """
         Rotate the label around a point.
 
@@ -91,7 +93,7 @@ class Label(PositionableImpl, LayerableImpl, LockableImpl, RepeatableImpl, Annot
         self.translate(+pivot)
         return self
 
-    def get_bounds(self) -> numpy.ndarray:
+    def get_bounds(self) -> NDArray[numpy.float64]:
         """
         Return the bounds of the label.
 

masque/pattern.py

@@ -9,21 +9,21 @@ import pickle
 from itertools import chain
 from collections import defaultdict
 
-import numpy        # type: ignore
+import numpy
 from numpy import inf
-from numpy.typing import ArrayLike
+from numpy.typing import NDArray, ArrayLike
 # .visualize imports matplotlib and matplotlib.collections
 
 from .subpattern import SubPattern
 from .shapes import Shape, Polygon
 from .label import Label
-from .utils import rotation_matrix_2d, vector2, normalize_mirror, AutoSlots, annotations_t
+from .utils import rotation_matrix_2d, normalize_mirror, AutoSlots, annotations_t
 from .error import PatternError, PatternLockedError
 from .traits import LockableImpl, AnnotatableImpl, Scalable, Mirrorable
 from .traits import Rotatable, Positionable
 
 
-visitor_function_t = Callable[['Pattern', Tuple['Pattern'], Dict, numpy.ndarray], 'Pattern']
+visitor_function_t = Callable[['Pattern', Tuple['Pattern'], Dict, NDArray[numpy.float64]], 'Pattern']
 
 
 P = TypeVar('P', bound='Pattern')
@@ -236,7 +236,7 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
             self: P,
             visit_before: visitor_function_t = None,
             visit_after: visitor_function_t = None,
-            transform: Union[numpy.ndarray, bool, None] = False,
+            transform: Union[ArrayLike, bool, None] = False,
             memo: Optional[Dict] = None,
             hierarchy: Tuple[P, ...] = (),
             ) -> P:
@@ -283,6 +283,8 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
 
         if transform is None or transform is True:
             transform = numpy.zeros(4)
+        elif transform is not False:
+            transform = numpy.array(transform)
 
         if self in hierarchy:
             raise PatternError('.dfs() called on pattern with circular reference')
@@ -441,7 +443,7 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
 
         return self
 
-    def as_polygons(self) -> List[numpy.ndarray]:
+    def as_polygons(self) -> List[NDArray[numpy.float64]]:
         """
         Represents the pattern as a list of polygons.
 
@@ -510,6 +512,7 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
             List of `(pat.name, pat)` tuples for all referenced Pattern objects
         """
         pats_by_id = self.referenced_patterns_by_id(**kwargs)
+        pat_list: List[Tuple[Optional[str], Optional['Pattern']]]
         pat_list = [(p.name if p is not None else None, p) for p in pats_by_id.values()]
         return pat_list
 
@@ -539,7 +542,7 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
                 ids.update(pat.subpatterns_by_id(include_none=include_none))
         return dict(ids)
 
-    def get_bounds(self) -> Union[numpy.ndarray, None]:
+    def get_bounds(self) -> Union[NDArray[numpy.float64], None]:
         """
         Return a `numpy.ndarray` containing `[[x_min, y_min], [x_max, y_max]]`, corresponding to the
          extent of the Pattern's contents in each dimension.
@@ -553,6 +556,7 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
 
         min_bounds = numpy.array((+inf, +inf))
         max_bounds = numpy.array((-inf, -inf))
+
         for entry in chain(self.shapes, self.subpatterns, self.labels):
             bounds = entry.get_bounds()
             if bounds is None:
@@ -655,7 +659,7 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
 
         return self
 
-    def translate_elements(self: P, offset: vector2) -> P:
+    def translate_elements(self: P, offset: ArrayLike) -> P:
         """
         Translates all shapes, label, and subpatterns by the given offset.
 
@@ -702,7 +706,7 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
             label.offset *= c
         return self
 
-    def rotate_around(self: P, pivot: vector2, rotation: float) -> P:
+    def rotate_around(self: P, pivot: ArrayLike, rotation: float) -> P:
         """
         Rotate the Pattern around the a location.
 
@@ -945,7 +949,7 @@ class Pattern(LockableImpl, AnnotatableImpl, Mirrorable, metaclass=AutoSlots):
 
     def visualize(
             self,
-            offset: vector2 = (0., 0.),
+            offset: ArrayLike = (0., 0.),
             line_color: str = 'k',
             fill_color: str = 'none',
             overdraw: bool = False,

masque/repetition.py

@@ -7,11 +7,11 @@ from typing import Union, Dict, Optional, Sequence, Any
 import copy
 from abc import ABCMeta, abstractmethod
 
-import numpy        # type: ignore
-from numpy.typing import ArrayLike
+import numpy
+from numpy.typing import ArrayLike, NDArray
 
 from .error import PatternError
-from .utils import rotation_matrix_2d, vector2, AutoSlots
+from .utils import rotation_matrix_2d, AutoSlots
 from .traits import LockableImpl, Copyable, Scalable, Rotatable, Mirrorable
 
 
@@ -23,7 +23,7 @@ class Repetition(Copyable, Rotatable, Mirrorable, Scalable, metaclass=ABCMeta):
 
     @property
     @abstractmethod
-    def displacements(self) -> numpy.ndarray:
+    def displacements(self) -> NDArray[numpy.float64]:
         """
         An Nx2 ndarray specifying all offsets generated by this repetition
         """
@@ -44,7 +44,7 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
                  '_a_count',
                  '_b_count')
 
-    _a_vector: numpy.ndarray
+    _a_vector: NDArray[numpy.float64]
     """ Vector `[x, y]` specifying the first lattice vector of the grid.
         Specifies center-to-center spacing between adjacent elements.
     """
@@ -52,7 +52,7 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
     _a_count: int
     """ Number of instances along the direction specified by the `a_vector` """
 
-    _b_vector: Optional[numpy.ndarray]
+    _b_vector: Optional[NDArray[numpy.float64]]
     """ Vector `[x, y]` specifying a second lattice vector for the grid.
         Specifies center-to-center spacing between adjacent elements.
         Can be `None` for a 1D array.
@@ -100,8 +100,8 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
             raise PatternError(f'Repetition has too-small b_count: {b_count}')
 
         object.__setattr__(self, 'locked', False)
-        self.a_vector = a_vector
-        self.b_vector = b_vector
+        self.a_vector = a_vector        # type: ignore     # setter handles type conversion
+        self.b_vector = b_vector        # type: ignore     # setter handles type conversion
         self.a_count = a_count
         self.b_count = b_count
         self.locked = locked
@@ -122,11 +122,11 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
 
     # a_vector property
     @property
-    def a_vector(self) -> numpy.ndarray:
+    def a_vector(self) -> NDArray[numpy.float64]:
         return self._a_vector
 
     @a_vector.setter
-    def a_vector(self, val: vector2):
+    def a_vector(self, val: ArrayLike) -> None:
         if not isinstance(val, numpy.ndarray):
             val = numpy.array(val, dtype=float)
 
@@ -136,11 +136,11 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
 
     # b_vector property
     @property
-    def b_vector(self) -> numpy.ndarray:
+    def b_vector(self) -> Optional[NDArray[numpy.float64]]:
         return self._b_vector
 
     @b_vector.setter
-    def b_vector(self, val: vector2):
+    def b_vector(self, val: ArrayLike) -> None:
         if not isinstance(val, numpy.ndarray):
             val = numpy.array(val, dtype=float, copy=True)
 
@@ -154,7 +154,7 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
         return self._a_count
 
     @a_count.setter
-    def a_count(self, val: int):
+    def a_count(self, val: int) -> None:
         if val != int(val):
             raise PatternError('a_count must be convertable to an int!')
         self._a_count = int(val)
@@ -165,13 +165,16 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
         return self._b_count
 
     @b_count.setter
-    def b_count(self, val: int):
+    def b_count(self, val: int) -> None:
         if val != int(val):
             raise PatternError('b_count must be convertable to an int!')
         self._b_count = int(val)
 
     @property
-    def displacements(self) -> numpy.ndarray:
+    def displacements(self) -> NDArray[numpy.float64]:
+        if self.b_vector is None:
+            return numpy.arange(self.a_count)[:, None] * self.a_vector[None, :]
+
         aa, bb = numpy.meshgrid(numpy.arange(self.a_count), numpy.arange(self.b_count), indexing='ij')
         return (aa.flatten()[:, None] * self.a_vector[None, :]
               + bb.flatten()[:, None] * self.b_vector[None, :])             # noqa
@@ -207,7 +210,7 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
             self.b_vector[1 - axis] *= -1
         return self
 
-    def get_bounds(self) -> Optional[numpy.ndarray]:
+    def get_bounds(self) -> Optional[NDArray[numpy.float64]]:
         """
         Return a `numpy.ndarray` containing `[[x_min, y_min], [x_max, y_max]]`, corresponding to the
          extent of the `Grid` in each dimension.
@@ -216,7 +219,7 @@ class Grid(LockableImpl, Repetition, metaclass=AutoSlots):
             `[[x_min, y_min], [x_max, y_max]]` or `None`
         """
         a_extent = self.a_vector * self.a_count
-        b_extent = self.b_vector * self.b_count if self.b_count != 0 else 0
+        b_extent = self.b_vector * self.b_count if (self.b_vector is not None) else 0       # type: Union[NDArray[numpy.float64], float]
 
         corners = ((0, 0), a_extent, b_extent, a_extent + b_extent)
         xy_min = numpy.min(corners, axis=0)
@@ -296,24 +299,26 @@ class Arbitrary(LockableImpl, Repetition, metaclass=AutoSlots):
                                        `[[x0, y0], [x1, y1], ...]`
     """
 
-    _displacements: numpy.ndarray
+    _displacements: NDArray[numpy.float64]
     """ List of vectors `[[x0, y0], [x1, y1], ...]` specifying the offsets
           of the instances.
     """
 
     @property
-    def displacements(self) -> numpy.ndarray:
+    def displacements(self) -> Any:     # TODO: mypy#3004   NDArray[numpy.float64]:
         return self._displacements
 
     @displacements.setter
-    def displacements(self, val: ArrayLike):
-        val = numpy.array(val, float)
-        val = numpy.sort(val.view([('', val.dtype)] * val.shape[1]), 0).view(val.dtype)    # sort rows
-        self._displacements = val
+    def displacements(self, val: ArrayLike) -> None:
+        vala: NDArray[numpy.float64] = numpy.array(vala, dtype=float)
+        vala = numpy.sort(vala.view([('', vala.dtype)] * vala.shape[1]), 0).view(vala.dtype)    # sort rows
+        self._displacements = vala
 
-    def __init__(self,
-                 displacements: ArrayLike,
-                 locked: bool = False,):
+    def __init__(
+            self,
+            displacements: ArrayLike,
+            locked: bool = False,
+            ) -> None:
         """
         Args:
             displacements: List of vectors (Nx2 ndarray) specifying displacements.
@@ -383,7 +388,7 @@ class Arbitrary(LockableImpl, Repetition, metaclass=AutoSlots):
         self.displacements[1 - axis] *= -1
         return self
 
-    def get_bounds(self) -> Optional[numpy.ndarray]:
+    def get_bounds(self) -> Optional[NDArray[numpy.float64]]:
         """
         Return a `numpy.ndarray` containing `[[x_min, y_min], [x_max, y_max]]`, corresponding to the
          extent of the `displacements` in each dimension.

masque/shapes/arc.py

@@ -1,14 +1,15 @@
-from typing import List, Dict, Optional, Sequence
+from typing import List, Dict, Optional, Sequence, Any
 import copy
 import math
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi
+from numpy.typing import NDArray, ArrayLike
 
 from . import Shape, Polygon, normalized_shape_tuple, DEFAULT_POLY_NUM_POINTS
 from .. import PatternError
 from ..repetition import Repetition
-from ..utils import is_scalar, vector2, layer_t, AutoSlots, annotations_t
+from ..utils import is_scalar, layer_t, AutoSlots, annotations_t
 from ..traits import LockableImpl
 
 
@@ -24,13 +25,13 @@ class Arc(Shape, metaclass=AutoSlots):
     __slots__ = ('_radii', '_angles', '_width', '_rotation',
                  'poly_num_points', 'poly_max_arclen')
 
-    _radii: numpy.ndarray
+    _radii: NDArray[numpy.float64]
     """ Two radii for defining an ellipse """
 
     _rotation: float
     """ Rotation (ccw, radians) from the x axis to the first radius """
 
-    _angles: numpy.ndarray
+    _angles: NDArray[numpy.float64]
     """ Start and stop angles (ccw, radians) for choosing an arc from the ellipse, measured from the first radius """
 
     _width: float
@@ -44,14 +45,14 @@ class Arc(Shape, metaclass=AutoSlots):
 
     # radius properties
     @property
-    def radii(self) -> numpy.ndarray:
+    def radii(self) -> Any:         #TODO mypy#3004   NDArray[numpy.float64]:
         """
         Return the radii `[rx, ry]`
         """
         return self._radii
 
     @radii.setter
-    def radii(self, val: vector2) -> None:
+    def radii(self, val: ArrayLike) -> None:
         val = numpy.array(val, dtype=float).flatten()
         if not val.size == 2:
             raise PatternError('Radii must have length 2')
@@ -81,7 +82,7 @@ class Arc(Shape, metaclass=AutoSlots):
 
     # arc start/stop angle properties
     @property
-    def angles(self) -> numpy.ndarray:
+    def angles(self) -> Any:            #TODO mypy#3004    NDArray[numpy.float64]:
         """
         Return the start and stop angles `[a_start, a_stop]`.
         Angles are measured from x-axis after rotation
@@ -92,7 +93,7 @@ class Arc(Shape, metaclass=AutoSlots):
         return self._angles
 
     @angles.setter
-    def angles(self, val: vector2) -> None:
+    def angles(self, val: ArrayLike) -> None:
         val = numpy.array(val, dtype=float).flatten()
         if not val.size == 2:
             raise PatternError('Angles must have length 2')
@@ -152,13 +153,13 @@ class Arc(Shape, metaclass=AutoSlots):
 
     def __init__(
             self,
-            radii: vector2,
-            angles: vector2,
+            radii: ArrayLike,
+            angles: ArrayLike,
             width: float,
             *,
             poly_num_points: Optional[int] = DEFAULT_POLY_NUM_POINTS,
             poly_max_arclen: Optional[float] = None,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0,
             mirrored: Sequence[bool] = (False, False),
             layer: layer_t = 0,
@@ -171,6 +172,9 @@ class Arc(Shape, metaclass=AutoSlots):
         LockableImpl.unlock(self)
         self.identifier = ()
         if raw:
+            assert(isinstance(radii, numpy.ndarray))
+            assert(isinstance(angles, numpy.ndarray))
+            assert(isinstance(offset, numpy.ndarray))
             self._radii = radii
             self._angles = angles
             self._width = width
@@ -241,7 +245,7 @@ class Arc(Shape, metaclass=AutoSlots):
 
         wh = self.width / 2.0
         if wh == r0 and r0 == r1:
-            thetas_inner = [0]      # Don't generate multiple vertices if we're at the origin
+            thetas_inner = numpy.zeros(1)      # Don't generate multiple vertices if we're at the origin
         else:
             thetas_inner = numpy.linspace(a_ranges[0][1], a_ranges[0][0], num_points, endpoint=True)
         thetas_outer = numpy.linspace(a_ranges[1][0], a_ranges[1][1], num_points, endpoint=True)
@@ -261,7 +265,7 @@ class Arc(Shape, metaclass=AutoSlots):
         poly = Polygon(xys, dose=self.dose, layer=self.layer, offset=self.offset, rotation=self.rotation)
         return [poly]
 
-    def get_bounds(self) -> numpy.ndarray:
+    def get_bounds(self) -> NDArray[numpy.float64]:
         '''
         Equation for rotated ellipse is
             `x = x0 + a * cos(t) * cos(rot) - b * sin(t) * sin(phi)`
@@ -367,7 +371,7 @@ class Arc(Shape, metaclass=AutoSlots):
                 (self.offset, scale / norm_value, rotation, False, self.dose),
                 lambda: Arc(radii=radii * norm_value, angles=angles, width=width * norm_value, layer=self.layer))
 
-    def get_cap_edges(self) -> numpy.ndarray:
+    def get_cap_edges(self) -> NDArray[numpy.float64]:
         '''
         Returns:
             ```
@@ -397,7 +401,7 @@ class Arc(Shape, metaclass=AutoSlots):
             maxs.append([xp, yp])
         return numpy.array([mins, maxs]) + self.offset
 
-    def _angles_to_parameters(self) -> numpy.ndarray:
+    def _angles_to_parameters(self) -> NDArray[numpy.float64]:
         '''
         Returns:
             "Eccentric anomaly" parameter ranges for the inner and outer edges, in the form

masque/shapes/circle.py

@@ -1,13 +1,14 @@
 from typing import List, Dict, Optional
 import copy
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi
+from numpy.typing import NDArray, ArrayLike
 
 from . import Shape, Polygon, normalized_shape_tuple, DEFAULT_POLY_NUM_POINTS
 from .. import PatternError
 from ..repetition import Repetition
-from ..utils import is_scalar, vector2, layer_t, AutoSlots, annotations_t
+from ..utils import is_scalar, layer_t, AutoSlots, annotations_t
 from ..traits import LockableImpl
 
 
@@ -48,7 +49,7 @@ class Circle(Shape, metaclass=AutoSlots):
             *,
             poly_num_points: Optional[int] = DEFAULT_POLY_NUM_POINTS,
             poly_max_arclen: Optional[float] = None,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             layer: layer_t = 0,
             dose: float = 1.0,
             repetition: Optional[Repetition] = None,
@@ -59,6 +60,7 @@ class Circle(Shape, metaclass=AutoSlots):
         LockableImpl.unlock(self)
         self.identifier = ()
         if raw:
+            assert(isinstance(offset, numpy.ndarray))
             self._radius = radius
             self._offset = offset
             self._repetition = repetition
@@ -98,7 +100,7 @@ class Circle(Shape, metaclass=AutoSlots):
             raise PatternError('Number of points and arclength left '
                                'unspecified (default was also overridden)')
 
-        n = []
+        n: List[float] = []
         if poly_num_points is not None:
             n += [poly_num_points]
         if poly_max_arclen is not None:
@@ -111,7 +113,7 @@ class Circle(Shape, metaclass=AutoSlots):
 
         return [Polygon(xys, offset=self.offset, dose=self.dose, layer=self.layer)]
 
-    def get_bounds(self) -> numpy.ndarray:
+    def get_bounds(self) -> NDArray[numpy.float64]:
         return numpy.vstack((self.offset - self.radius,
                              self.offset + self.radius))
 

masque/shapes/ellipse.py

@@ -1,14 +1,15 @@
-from typing import List, Dict, Sequence, Optional
+from typing import List, Dict, Sequence, Optional, Any
 import copy
 import math
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi
+from numpy.typing import ArrayLike, NDArray
 
 from . import Shape, Polygon, normalized_shape_tuple, DEFAULT_POLY_NUM_POINTS
 from .. import PatternError
 from ..repetition import Repetition
-from ..utils import is_scalar, rotation_matrix_2d, vector2, layer_t, AutoSlots, annotations_t
+from ..utils import is_scalar, rotation_matrix_2d, layer_t, AutoSlots, annotations_t
 from ..traits import LockableImpl
 
 
@@ -20,7 +21,7 @@ class Ellipse(Shape, metaclass=AutoSlots):
     __slots__ = ('_radii', '_rotation',
                  'poly_num_points', 'poly_max_arclen')
 
-    _radii: numpy.ndarray
+    _radii: NDArray[numpy.float64]
     """ Ellipse radii """
 
     _rotation: float
@@ -34,14 +35,14 @@ class Ellipse(Shape, metaclass=AutoSlots):
 
     # radius properties
     @property
-    def radii(self) -> numpy.ndarray:
+    def radii(self) -> Any:         #TODO mypy#3004  NDArray[numpy.float64]:
         """
         Return the radii `[rx, ry]`
         """
         return self._radii
 
     @radii.setter
-    def radii(self, val: vector2) -> None:
+    def radii(self, val: ArrayLike) -> None:
         val = numpy.array(val).flatten()
         if not val.size == 2:
             raise PatternError('Radii must have length 2')
@@ -89,11 +90,11 @@ class Ellipse(Shape, metaclass=AutoSlots):
 
     def __init__(
             self,
-            radii: vector2,
+            radii: ArrayLike,
             *,
             poly_num_points: Optional[int] = DEFAULT_POLY_NUM_POINTS,
             poly_max_arclen: Optional[float] = None,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0,
             mirrored: Sequence[bool] = (False, False),
             layer: layer_t = 0,
@@ -106,6 +107,8 @@ class Ellipse(Shape, metaclass=AutoSlots):
         LockableImpl.unlock(self)
         self.identifier = ()
         if raw:
+            assert(isinstance(radii, numpy.ndarray))
+            assert(isinstance(offset, numpy.ndarray))
             self._radii = radii
             self._offset = offset
             self._rotation = rotation
@@ -173,7 +176,7 @@ class Ellipse(Shape, metaclass=AutoSlots):
         poly = Polygon(xys, dose=self.dose, layer=self.layer, offset=self.offset, rotation=self.rotation)
         return [poly]
 
-    def get_bounds(self) -> numpy.ndarray:
+    def get_bounds(self) -> NDArray[numpy.float64]:
         rot_radii = numpy.dot(rotation_matrix_2d(self.rotation), self.radii)
         return numpy.vstack((self.offset - rot_radii[0],
                              self.offset + rot_radii[1]))

masque/shapes/path.py

@@ -1,15 +1,15 @@
-from typing import List, Tuple, Dict, Optional, Sequence
+from typing import List, Tuple, Dict, Optional, Sequence, Any
 import copy
 from enum import Enum
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi, inf
-from numpy.typing import ArrayLike
+from numpy.typing import NDArray, ArrayLike
 
 from . import Shape, normalized_shape_tuple, Polygon, Circle
 from .. import PatternError
 from ..repetition import Repetition
-from ..utils import is_scalar, rotation_matrix_2d, vector2, layer_t, AutoSlots
+from ..utils import is_scalar, rotation_matrix_2d, layer_t, AutoSlots
 from ..utils import remove_colinear_vertices, remove_duplicate_vertices, annotations_t
 from ..traits import LockableImpl
 
@@ -30,10 +30,10 @@ class Path(Shape, metaclass=AutoSlots):
     A normalized_form(...) is available, but can be quite slow with lots of vertices.
     """
     __slots__ = ('_vertices', '_width', '_cap', '_cap_extensions')
-    _vertices: numpy.ndarray
+    _vertices: NDArray[numpy.float64]
     _width: float
     _cap: PathCap
-    _cap_extensions: Optional[numpy.ndarray]
+    _cap_extensions: Optional[NDArray[numpy.float64]]
 
     Cap = PathCap
 
@@ -73,7 +73,7 @@ class Path(Shape, metaclass=AutoSlots):
 
     # cap_extensions property
     @property
-    def cap_extensions(self) -> Optional[numpy.ndarray]:
+    def cap_extensions(self) -> Optional[Any]:  #TODO mypy#3004  NDArray[numpy.float64]]:
         """
         Path end-cap extension
 
@@ -83,7 +83,7 @@ class Path(Shape, metaclass=AutoSlots):
         return self._cap_extensions
 
     @cap_extensions.setter
-    def cap_extensions(self, vals: Optional[numpy.ndarray]) -> None:
+    def cap_extensions(self, vals: Optional[ArrayLike]) -> None:
         custom_caps = (PathCap.SquareCustom,)
         if self.cap in custom_caps:
             if vals is None:
@@ -96,7 +96,7 @@ class Path(Shape, metaclass=AutoSlots):
 
     # vertices property
     @property
-    def vertices(self) -> numpy.ndarray:
+    def vertices(self) -> Any:  #TODO mypy#3004  NDArray[numpy.float64]]:
         """
         Vertices of the path (Nx2 ndarray: `[[x0, y0], [x1, y1], ...]`)
         """
@@ -113,7 +113,7 @@ class Path(Shape, metaclass=AutoSlots):
 
     # xs property
     @property
-    def xs(self) -> numpy.ndarray:
+    def xs(self) -> NDArray[numpy.float64]:
         """
         All vertex x coords as a 1D ndarray
         """
@@ -128,7 +128,7 @@ class Path(Shape, metaclass=AutoSlots):
 
     # ys property
     @property
-    def ys(self) -> numpy.ndarray:
+    def ys(self) -> NDArray[numpy.float64]:
         """
         All vertex y coords as a 1D ndarray
         """
@@ -148,7 +148,7 @@ class Path(Shape, metaclass=AutoSlots):
             *,
             cap: PathCap = PathCap.Flush,
             cap_extensions: Optional[ArrayLike] = None,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0,
             mirrored: Sequence[bool] = (False, False),
             layer: layer_t = 0,
@@ -163,6 +163,9 @@ class Path(Shape, metaclass=AutoSlots):
 
         self.identifier = ()
         if raw:
+            assert(isinstance(vertices, numpy.ndarray))
+            assert(isinstance(offset, numpy.ndarray))
+            assert(isinstance(cap_extensions, numpy.ndarray) or cap_extensions is None)
             self._vertices = vertices
             self._offset = offset
             self._repetition = repetition
@@ -199,11 +202,11 @@ class Path(Shape, metaclass=AutoSlots):
 
     @staticmethod
     def travel(
-            travel_pairs: Tuple[Tuple[float, float]],
+            travel_pairs: Sequence[Tuple[float, float]],
             width: float = 0.0,
             cap: PathCap = PathCap.Flush,
             cap_extensions: Optional[Tuple[float, float]] = None,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0,
             mirrored: Sequence[bool] = (False, False),
             layer: layer_t = 0,
@@ -236,7 +239,7 @@ class Path(Shape, metaclass=AutoSlots):
         #TODO: needs testing
         direction = numpy.array([1, 0])
 
-        verts = [[0, 0]]
+        verts = [numpy.zeros(2)]
         for angle, distance in travel_pairs:
             direction = numpy.dot(rotation_matrix_2d(angle), direction.T).T
             verts.append(verts[-1] + direction * distance)
@@ -319,7 +322,7 @@ class Path(Shape, metaclass=AutoSlots):
 
         return polys
 
-    def get_bounds(self) -> numpy.ndarray:
+    def get_bounds(self) -> NDArray[numpy.float64]:
         if self.cap == PathCap.Circle:
             bounds = self.offset + numpy.vstack((numpy.min(self.vertices, axis=0) - self.width / 2,
                                                  numpy.max(self.vertices, axis=0) + self.width / 2))
@@ -409,10 +412,11 @@ class Path(Shape, metaclass=AutoSlots):
         self.vertices = remove_colinear_vertices(self.vertices, closed_path=False)
         return self
 
-    def _calculate_cap_extensions(self) -> numpy.ndarray:
+    def _calculate_cap_extensions(self) -> NDArray[numpy.float64]:
         if self.cap == PathCap.Square:
             extensions = numpy.full(2, self.width / 2)
         elif self.cap == PathCap.SquareCustom:
+            assert(isinstance(self.cap_extensions, numpy.ndarray))
             extensions = self.cap_extensions
         else:
             # Flush or Circle

masque/shapes/polygon.py

@@ -1,14 +1,14 @@
-from typing import List, Dict, Optional, Sequence
+from typing import List, Dict, Optional, Sequence, Any
 import copy
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi
-from numpy.typing import ArrayLike
+from numpy.typing import NDArray, ArrayLike
 
 from . import Shape, normalized_shape_tuple
 from .. import PatternError
 from ..repetition import Repetition
-from ..utils import is_scalar, rotation_matrix_2d, vector2, layer_t, AutoSlots
+from ..utils import is_scalar, rotation_matrix_2d, layer_t, AutoSlots
 from ..utils import remove_colinear_vertices, remove_duplicate_vertices, annotations_t
 from ..traits import LockableImpl
 
@@ -22,12 +22,12 @@ class Polygon(Shape, metaclass=AutoSlots):
     """
     __slots__ = ('_vertices',)
 
-    _vertices: numpy.ndarray
+    _vertices: NDArray[numpy.float64]
     """ Nx2 ndarray of vertices `[[x0, y0], [x1, y1], ...]` """
 
     # vertices property
     @property
-    def vertices(self) -> numpy.ndarray:
+    def vertices(self) -> Any:        #TODO mypy#3004   NDArray[numpy.float64]:
         """
         Vertices of the polygon (Nx2 ndarray: `[[x0, y0], [x1, y1], ...]`)
         """
@@ -44,7 +44,7 @@ class Polygon(Shape, metaclass=AutoSlots):
 
     # xs property
     @property
-    def xs(self) -> numpy.ndarray:
+    def xs(self) -> NDArray[numpy.float64]:
         """
         All vertex x coords as a 1D ndarray
         """
@@ -59,7 +59,7 @@ class Polygon(Shape, metaclass=AutoSlots):
 
     # ys property
     @property
-    def ys(self) -> numpy.ndarray:
+    def ys(self) -> NDArray[numpy.float64]:
         """
         All vertex y coords as a 1D ndarray
         """
@@ -76,7 +76,7 @@ class Polygon(Shape, metaclass=AutoSlots):
             self,
             vertices: ArrayLike,
             *,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0.0,
             mirrored: Sequence[bool] = (False, False),
             layer: layer_t = 0,
@@ -89,6 +89,8 @@ class Polygon(Shape, metaclass=AutoSlots):
         LockableImpl.unlock(self)
         self.identifier = ()
         if raw:
+            assert(isinstance(vertices, numpy.ndarray))
+            assert(isinstance(offset, numpy.ndarray))
             self._vertices = vertices
             self._offset = offset
             self._repetition = repetition
@@ -120,7 +122,7 @@ class Polygon(Shape, metaclass=AutoSlots):
             side_length: float,
             *,
             rotation: float = 0.0,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             layer: layer_t = 0,
             dose: float = 1.0,
             repetition: Optional[Repetition] = None,
@@ -155,7 +157,7 @@ class Polygon(Shape, metaclass=AutoSlots):
             ly: float,
             *,
             rotation: float = 0,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             layer: layer_t = 0,
             dose: float = 1.0,
             repetition: Optional[Repetition] = None,
@@ -291,7 +293,7 @@ class Polygon(Shape, metaclass=AutoSlots):
             side_length: Optional[float] = None,
             inner_radius: Optional[float] = None,
             regular: bool = True,
-            center: vector2 = (0.0, 0.0),
+            center: ArrayLike = (0.0, 0.0),
             rotation: float = 0.0,
             layer: layer_t = 0,
             dose: float = 1.0,
@@ -353,7 +355,7 @@ class Polygon(Shape, metaclass=AutoSlots):
             ) -> List['Polygon']:
         return [copy.deepcopy(self)]
 
-    def get_bounds(self) -> numpy.ndarray:
+    def get_bounds(self) -> NDArray[numpy.float64]:
         return numpy.vstack((self.offset + numpy.min(self.vertices, axis=0),
                              self.offset + numpy.max(self.vertices, axis=0)))
 

masque/shapes/shape.py

@@ -1,8 +1,8 @@
 from typing import List, Tuple, Callable, TypeVar, Optional, TYPE_CHECKING
 from abc import ABCMeta, abstractmethod
 
-import numpy        # type: ignore
-from numpy.typing import ArrayLike
+import numpy
+from numpy.typing import NDArray, ArrayLike
 
 from ..traits import (PositionableImpl, LayerableImpl, DoseableImpl,
                       Rotatable, Mirrorable, Copyable, Scalable,
@@ -15,7 +15,7 @@ if TYPE_CHECKING:
 
 # Type definitions
 normalized_shape_tuple = Tuple[Tuple,
-                               Tuple[numpy.ndarray, float, float, bool, float],
+                               Tuple[NDArray[numpy.float64], float, float, bool, float],
                                Callable[[], 'Shape']]
 
 # ## Module-wide defaults
@@ -117,12 +117,16 @@ class Shape(PositionableImpl, LayerableImpl, DoseableImpl, Rotatable, Mirrorable
         """
         from . import Polygon
 
-        grid_x = numpy.unique(grid_x)
-        grid_y = numpy.unique(grid_y)
+        gx = numpy.unique(grid_x)
+        gy = numpy.unique(grid_y)
 
         polygon_contours = []
         for polygon in self.to_polygons():
-            mins, maxs = polygon.get_bounds()
+            bounds = polygon.get_bounds()
+            if not bounds:
+                continue
+
+            mins, maxs = bounds
 
             vertex_lists = []
             p_verts = polygon.vertices + polygon.offset
@@ -130,12 +134,12 @@ class Shape(PositionableImpl, LayerableImpl, DoseableImpl, Rotatable, Mirrorable
                 dv = v_next - v
 
                 # Find x-index bounds for the line      # TODO: fix this and err_xmin/xmax for grids smaller than the line / shape
-                gxi_range = numpy.digitize([v[0], v_next[0]], grid_x)
-                gxi_min = numpy.min(gxi_range - 1).clip(0, len(grid_x) - 1)
-                gxi_max = numpy.max(gxi_range).clip(0, len(grid_x))
+                gxi_range = numpy.digitize([v[0], v_next[0]], gx)
+                gxi_min = numpy.min(gxi_range - 1).clip(0, len(gx) - 1)
+                gxi_max = numpy.max(gxi_range).clip(0, len(gx))
 
-                err_xmin = (min(v[0], v_next[0]) - grid_x[gxi_min]) / (grid_x[gxi_min + 1] - grid_x[gxi_min])
-                err_xmax = (max(v[0], v_next[0]) - grid_x[gxi_max - 1]) / (grid_x[gxi_max] - grid_x[gxi_max - 1])
+                err_xmin = (min(v[0], v_next[0]) - gx[gxi_min]) / (gx[gxi_min + 1] - gx[gxi_min])
+                err_xmax = (max(v[0], v_next[0]) - gx[gxi_max - 1]) / (gx[gxi_max] - gx[gxi_max - 1])
 
                 if err_xmin >= 0.5:
                     gxi_min += 1
@@ -146,32 +150,32 @@ class Shape(PositionableImpl, LayerableImpl, DoseableImpl, Rotatable, Mirrorable
                     # Vertical line, don't calculate slope
                     xi = [gxi_min, gxi_max - 1]
                     ys = numpy.array([v[1], v_next[1]])
-                    yi = numpy.digitize(ys, grid_y).clip(1, len(grid_y) - 1)
-                    err_y = (ys - grid_y[yi]) / (grid_y[yi] - grid_y[yi - 1])
+                    yi = numpy.digitize(ys, gy).clip(1, len(gy) - 1)
+                    err_y = (ys - gy[yi]) / (gy[yi] - gy[yi - 1])
                     yi[err_y < 0.5] -= 1
 
-                    segment = numpy.column_stack((grid_x[xi], grid_y[yi]))
+                    segment = numpy.column_stack((gx[xi], gy[yi]))
                     vertex_lists.append(segment)
                     continue
 
                 m = dv[1] / dv[0]
 
-                def get_grid_inds(xes: numpy.ndarray) -> numpy.ndarray:
+                def get_grid_inds(xes: ArrayLike) -> NDArray[numpy.float64]:
                     ys = m * (xes - v[0]) + v[1]
 
                     # (inds - 1) is the index of the y-grid line below the edge's intersection with the x-grid
-                    inds = numpy.digitize(ys, grid_y).clip(1, len(grid_y) - 1)
+                    inds = numpy.digitize(ys, gy).clip(1, len(gy) - 1)
 
                     # err is what fraction of the cell upwards we have to go to reach our y
                     #   (can be negative at bottom edge due to clip above)
-                    err = (ys - grid_y[inds - 1]) / (grid_y[inds] - grid_y[inds - 1])
+                    err = (ys - gy[inds - 1]) / (gy[inds] - gy[inds - 1])
 
                     # now set inds to the index of the nearest y-grid line
                     inds[err < 0.5] -= 1
                     return inds
 
                 # Find the y indices on all x gridlines
-                xs = grid_x[gxi_min:gxi_max]
+                xs = gx[gxi_min:gxi_max]
                 inds = get_grid_inds(xs)
 
                 # Find y-intersections for x-midpoints
@@ -186,7 +190,7 @@ class Shape(PositionableImpl, LayerableImpl, DoseableImpl, Rotatable, Mirrorable
                 yinds[1::3] = inds2
                 yinds[2::3] = inds2
 
-                vlist = numpy.column_stack((grid_x[xinds], grid_y[yinds]))
+                vlist = numpy.column_stack((gx[xinds], gy[yinds]))
                 if dv[0] < 0:
                     vlist = vlist[::-1]
 
@@ -249,23 +253,27 @@ class Shape(PositionableImpl, LayerableImpl, DoseableImpl, Rotatable, Mirrorable
         import skimage.measure      # type: ignore
         import float_raster
 
-        grid_x = numpy.unique(grid_x)
-        grid_y = numpy.unique(grid_y)
+        grx = numpy.unique(grid_x)
+        gry = numpy.unique(grid_y)
 
         polygon_contours = []
         for polygon in self.to_polygons():
             # Get rid of unused gridlines (anything not within 2 lines of the polygon bounds)
-            mins, maxs = polygon.get_bounds()
-            keep_x = numpy.logical_and(grid_x > mins[0], grid_x < maxs[0])
-            keep_y = numpy.logical_and(grid_y > mins[1], grid_y < maxs[1])
+            bounds = polygon.get_bounds()
+            if not bounds:
+                continue
+
+            mins, maxs = bounds
+            keep_x = numpy.logical_and(grx > mins[0], grx < maxs[0])
+            keep_y = numpy.logical_and(gry > mins[1], gry < maxs[1])
             for k in (keep_x, keep_y):
                 for s in (1, 2):
                     k[s:] += k[:-s]
                     k[:-s] += k[s:]
                 k = k > 0
 
-            gx = grid_x[keep_x]
-            gy = grid_y[keep_y]
+            gx = grx[keep_x]
+            gy = gry[keep_y]
 
             if len(gx) == 0 or len(gy) == 0:
                 continue
@@ -286,8 +294,8 @@ class Shape(PositionableImpl, LayerableImpl, DoseableImpl, Rotatable, Mirrorable
                 # /2 deals with supersampling
                 # +.5 deals with the fact that our 0-edge becomes -.5 in the super-sampled contour output
                 snapped_contour = numpy.round((contour + .5) / 2).astype(int)
-                vertices = numpy.hstack((grid_x[snapped_contour[:, None, 0] + offset_i[0]],
-                                         grid_y[snapped_contour[:, None, 1] + offset_i[1]]))
+                vertices = numpy.hstack((grx[snapped_contour[:, None, 0] + offset_i[0]],
+                                         gry[snapped_contour[:, None, 1] + offset_i[1]]))
 
                 manhattan_polygons.append(Polygon(
                     vertices=vertices,

masque/shapes/text.py

@@ -1,14 +1,15 @@
-from typing import List, Tuple, Dict, Sequence, Optional
+from typing import List, Tuple, Dict, Sequence, Optional, Any
 import copy
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi, inf
+from numpy.typing import NDArray, ArrayLike
 
 from . import Shape, Polygon, normalized_shape_tuple
 from .. import PatternError
 from ..repetition import Repetition
 from ..traits import RotatableImpl
-from ..utils import is_scalar, vector2, get_bit, normalize_mirror, layer_t, AutoSlots
+from ..utils import is_scalar, get_bit, normalize_mirror, layer_t, AutoSlots
 from ..utils import annotations_t
 from ..traits import LockableImpl
 
@@ -26,7 +27,7 @@ class Text(RotatableImpl, Shape, metaclass=AutoSlots):
 
     _string: str
     _height: float
-    _mirrored: numpy.ndarray        # ndarray[bool]
+    _mirrored: NDArray[numpy.bool_]
     font_path: str
 
     # vertices property
@@ -51,7 +52,7 @@ class Text(RotatableImpl, Shape, metaclass=AutoSlots):
 
     # Mirrored property
     @property
-    def mirrored(self) -> numpy.ndarray:        # ndarray[bool]
+    def mirrored(self) -> Any:   #TODO mypy#3004  NDArray[numpy.bool_]:
         return self._mirrored
 
     @mirrored.setter
@@ -66,9 +67,9 @@ class Text(RotatableImpl, Shape, metaclass=AutoSlots):
             height: float,
             font_path: str,
             *,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0.0,
-            mirrored: Tuple[bool, bool] = (False, False),
+            mirrored: ArrayLike = (False, False),
             layer: layer_t = 0,
             dose: float = 1.0,
             repetition: Optional[Repetition] = None,
@@ -79,6 +80,8 @@ class Text(RotatableImpl, Shape, metaclass=AutoSlots):
         LockableImpl.unlock(self)
         self.identifier = ()
         if raw:
+            assert(isinstance(offset, numpy.ndarray))
+            assert(isinstance(mirrored, numpy.ndarray))
             self._offset = offset
             self._layer = layer
             self._dose = dose
@@ -155,7 +158,7 @@ class Text(RotatableImpl, Shape, metaclass=AutoSlots):
                              mirrored=(mirror_x, False),
                              layer=self.layer))
 
-    def get_bounds(self) -> numpy.ndarray:
+    def get_bounds(self) -> NDArray[numpy.float64]:
         # rotation makes this a huge pain when using slot.advance and glyph.bbox(), so
         #  just convert to polygons instead
         bounds = numpy.array([[+inf, +inf], [-inf, -inf]])
@@ -201,7 +204,7 @@ def get_char_as_polygons(
     outline = slot.outline
 
     start = 0
-    all_verts, all_codes = [], []
+    all_verts_list, all_codes = [], []
     for end in outline.contours:
         points = outline.points[start:end + 1]
         points.append(points[0])
@@ -238,11 +241,11 @@ def get_char_as_polygons(
                     codes.extend([Path.CURVE3, Path.CURVE3])
                 verts.append(segment[-1])
                 codes.append(Path.CURVE3)
-        all_verts.extend(verts)
+        all_verts_list.extend(verts)
         all_codes.extend(codes)
         start = end + 1
 
-    all_verts = numpy.array(all_verts) / resolution
+    all_verts = numpy.array(all_verts_list) / resolution
 
     advance = slot.advance.x / resolution
 

masque/subpattern.py

@@ -7,11 +7,12 @@
 from typing import Dict, Tuple, Optional, Sequence, TYPE_CHECKING, Any, TypeVar
 import copy
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi
+from numpy.typing import NDArray, ArrayLike
 
 from .error import PatternError
-from .utils import is_scalar, vector2, AutoSlots, annotations_t
+from .utils import is_scalar, AutoSlots, annotations_t
 from .repetition import Repetition
 from .traits import (PositionableImpl, DoseableImpl, RotatableImpl, ScalableImpl,
                      Mirrorable, PivotableImpl, Copyable, LockableImpl, RepeatableImpl,
@@ -40,7 +41,7 @@ class SubPattern(PositionableImpl, DoseableImpl, RotatableImpl, ScalableImpl, Mi
     _pattern: Optional['Pattern']
     """ The `Pattern` being instanced """
 
-    _mirrored: numpy.ndarray        # ndarray[bool]
+    _mirrored: NDArray[numpy.bool_]
     """ Whether to mirror the instance across the x and/or y axes. """
 
     identifier: Tuple[Any, ...]
@@ -50,7 +51,7 @@ class SubPattern(PositionableImpl, DoseableImpl, RotatableImpl, ScalableImpl, Mi
             self,
             pattern: Optional['Pattern'],
             *,
-            offset: vector2 = (0.0, 0.0),
+            offset: ArrayLike = (0.0, 0.0),
             rotation: float = 0.0,
             mirrored: Optional[Sequence[bool]] = None,
             dose: float = 1.0,
@@ -113,7 +114,7 @@ class SubPattern(PositionableImpl, DoseableImpl, RotatableImpl, ScalableImpl, Mi
         return self._pattern
 
     @pattern.setter
-    def pattern(self, val: Optional['Pattern']):
+    def pattern(self, val: Optional['Pattern']) -> None:
         from .pattern import Pattern
         if val is not None and not isinstance(val, Pattern):
             raise PatternError(f'Provided pattern {val} is not a Pattern object or None!')
@@ -121,11 +122,11 @@ class SubPattern(PositionableImpl, DoseableImpl, RotatableImpl, ScalableImpl, Mi
 
     # Mirrored property
     @property
-    def mirrored(self) -> numpy.ndarray:        # ndarray[bool]
+    def mirrored(self) -> Any:   #TODO mypy#3004  NDArray[numpy.bool_]:
         return self._mirrored
 
     @mirrored.setter
-    def mirrored(self, val: Sequence[bool]):
+    def mirrored(self, val: ArrayLike) -> None:
         if is_scalar(val):
             raise PatternError('Mirrored must be a 2-element list of booleans')
         self._mirrored = numpy.array(val, dtype=bool, copy=True)
@@ -167,7 +168,7 @@ class SubPattern(PositionableImpl, DoseableImpl, RotatableImpl, ScalableImpl, Mi
             self.repetition.mirror(axis)
         return self
 
-    def get_bounds(self) -> Optional[numpy.ndarray]:
+    def get_bounds(self) -> Optional[NDArray[numpy.float64]]:
         """
         Return a `numpy.ndarray` containing `[[x_min, y_min], [x_max, y_max]]`, corresponding to the
          extent of the `SubPattern` in each dimension.

masque/traits/positionable.py

@@ -1,11 +1,12 @@
 # TODO top-level comment about how traits should set __slots__ = (), and how to use AutoSlots
 
-from typing import TypeVar
+from typing import TypeVar, Any, Optional
 from abc import ABCMeta, abstractmethod
-import numpy        # type: ignore
+
+import numpy
+from numpy.typing import NDArray, ArrayLike
 
 from ..error import MasqueError
-from ..utils import vector2
 
 
 T = TypeVar('T', bound='Positionable')
@@ -23,7 +24,7 @@ class Positionable(metaclass=ABCMeta):
     '''
     @property
     @abstractmethod
-    def offset(self) -> numpy.ndarray:
+    def offset(self) -> NDArray[numpy.float64]:
         """
         [x, y] offset
         """
@@ -31,21 +32,11 @@ class Positionable(metaclass=ABCMeta):
 
 #    @offset.setter
 #    @abstractmethod
-#    def offset(self, val: vector2):
+#    def offset(self, val: ArrayLike):
 #        pass
 
-    '''
-    --- Abstract methods
-    '''
     @abstractmethod
-    def get_bounds(self) -> numpy.ndarray:
-        """
-        Returns `[[x_min, y_min], [x_max, y_max]]` which specify a minimal bounding box for the entity.
-        """
-        pass
-
-    @abstractmethod
-    def set_offset(self: T, offset: vector2) -> T:
+    def set_offset(self: T, offset: ArrayLike) -> T:
         """
         Set the offset
 
@@ -58,7 +49,7 @@ class Positionable(metaclass=ABCMeta):
         pass
 
     @abstractmethod
-    def translate(self: T, offset: vector2) -> T:
+    def translate(self: T, offset: ArrayLike) -> T:
         """
         Translate the entity by the given offset
 
@@ -70,6 +61,13 @@ class Positionable(metaclass=ABCMeta):
         """
         pass
 
+    @abstractmethod
+    def get_bounds(self) -> Optional[NDArray[numpy.float64]]:
+        """
+        Returns `[[x_min, y_min], [x_max, y_max]]` which specify a minimal bounding box for the entity.
+        """
+        pass
+
 
 class PositionableImpl(Positionable, metaclass=ABCMeta):
     """
@@ -77,7 +75,7 @@ class PositionableImpl(Positionable, metaclass=ABCMeta):
     """
     __slots__ = ()
 
-    _offset: numpy.ndarray
+    _offset: NDArray[numpy.float64]
     """ `[x_offset, y_offset]` """
 
     '''
@@ -85,14 +83,14 @@ class PositionableImpl(Positionable, metaclass=ABCMeta):
     '''
     # offset property
     @property
-    def offset(self) -> numpy.ndarray:
+    def offset(self) -> Any:  #TODO mypy#3003  NDArray[numpy.float64]:
         """
         [x, y] offset
         """
         return self._offset
 
     @offset.setter
-    def offset(self, val: vector2):
+    def offset(self, val: ArrayLike) -> None:
         if not isinstance(val, numpy.ndarray) or val.dtype != numpy.float64:
             val = numpy.array(val, dtype=float)
 
@@ -103,12 +101,12 @@ class PositionableImpl(Positionable, metaclass=ABCMeta):
     '''
     ---- Methods
     '''
-    def set_offset(self: I, offset: vector2) -> I:
+    def set_offset(self: I, offset: ArrayLike) -> I:
         self.offset = offset
         return self
 
-    def translate(self: I, offset: vector2) -> I:
-        self._offset += offset
+    def translate(self: I, offset: ArrayLike) -> I:
+        self._offset += offset   # type: ignore         # NDArray += ArrayLike should be fine??
         return self
 
     def _lock(self: I) -> I:

masque/traits/rotatable.py

@@ -1,12 +1,13 @@
 from typing import TypeVar
 from abc import ABCMeta, abstractmethod
 
-import numpy        # type: ignore
+import numpy
 from numpy import pi
+from numpy.typing import ArrayLike, NDArray
 
 #from .positionable import Positionable
 from ..error import MasqueError
-from ..utils import is_scalar, rotation_matrix_2d, vector2
+from ..utils import is_scalar, rotation_matrix_2d
 
 T = TypeVar('T', bound='Rotatable')
 I = TypeVar('I', bound='RotatableImpl')
@@ -89,7 +90,7 @@ class Pivotable(metaclass=ABCMeta):
     __slots__ = ()
 
     @abstractmethod
-    def rotate_around(self: P, pivot: vector2, rotation: float) -> P:
+    def rotate_around(self: P, pivot: ArrayLike, rotation: float) -> P:
         """
         Rotate the object around a point.
 
@@ -109,11 +110,11 @@ class PivotableImpl(Pivotable, metaclass=ABCMeta):
     """
     __slots__ = ()
 
-    def rotate_around(self: J, pivot: vector2, rotation: float) -> J:
+    def rotate_around(self: J, pivot: ArrayLike, rotation: float) -> J:
         pivot = numpy.array(pivot, dtype=float)
         self.translate(-pivot)
         self.rotate(rotation)
-        self.offset = numpy.dot(rotation_matrix_2d(rotation), self.offset)
+        self.offset = numpy.dot(rotation_matrix_2d(rotation), self.offset)      #type: ignore #TODO: mypy#3004
         self.translate(+pivot)
         return self
 

masque/utils.py

@@ -4,12 +4,11 @@ Various helper functions
 from typing import Any, Union, Tuple, Sequence, Dict, List
 from abc import ABCMeta
 
-import numpy        # type: ignore
-from numpy.typing import ArrayLike
+import numpy
+from numpy.typing import NDArray, ArrayLike
 
 
 # Type definitions
-vector2 = ArrayLike
 layer_t = Union[int, Tuple[int, int], str]
 annotations_t = Dict[str, List[Union[int, float, str]]]
 
@@ -57,7 +56,7 @@ def set_bit(bit_string: Any, bit_id: int, value: bool) -> Any:
     return bit_string
 
 
-def rotation_matrix_2d(theta: float) -> numpy.ndarray:
+def rotation_matrix_2d(theta: float) -> NDArray[numpy.float64]:
     """
     2D rotation matrix for rotating counterclockwise around the origin.
 
@@ -90,7 +89,7 @@ def normalize_mirror(mirrored: Sequence[bool]) -> Tuple[bool, float]:
     return mirror_x, angle
 
 
-def remove_duplicate_vertices(vertices: ArrayLike, closed_path: bool = True) -> numpy.ndarray:
+def remove_duplicate_vertices(vertices: ArrayLike, closed_path: bool = True) -> NDArray[numpy.float64]:
     """
     Given a list of vertices, remove any consecutive duplicates.
 
@@ -102,13 +101,14 @@ def remove_duplicate_vertices(vertices: ArrayLike, closed_path: bool = True) ->
     Returns:
         `vertices` with no consecutive duplicates.
     """
+    vertices = numpy.array(vertices)
     duplicates = (vertices == numpy.roll(vertices, 1, axis=0)).all(axis=1)
     if not closed_path:
         duplicates[0] = False
     return vertices[~duplicates]
 
 
-def remove_colinear_vertices(vertices: ArrayLike, closed_path: bool = True) -> numpy.ndarray:
+def remove_colinear_vertices(vertices: ArrayLike, closed_path: bool = True) -> NDArray[numpy.float64]:
     """
     Given a list of vertices, remove any superflous vertices (i.e.
         those which lie along the line formed by their neighbors)